Senior Prognostics and Health Management Engineer

GIS conducts applied research in the area of sustainable manufacturing, and also provides technical assistance in a wide variety of areas to industry. We are looking for an engineer or scientist with a strong experimental and analytical background to support existing research programs in prognostics and health management (PHM), and data analytics. Our two primary application areas are transportation systems, including DoD systems, manufacturing equipment and processes, and embedded product monitoring. In our work environment, researchers work in multi-disciplinary teams on a wide variety of different types of products and technologies, work with undergraduate and graduate students, and are engaged in collaborative research with leading companies. The ideal candidate will have worked in the development of PHM systems in industry or government positions, or completed Masters or PhD level research focused on PHM technologies.
Primary Responsibilities
- Conduct and manage research and development projects focused on PHM or data analytics in a variety of different application areas.
- Analyze the function and performance of electro-mechanical systems including failure modes.
- Develop models and algorithms to assess the condition of electro-mechanical systems. The candidate should be comfortable with empirical lab or field work, as well as with simulation and modeling tools in their educational domain area.
- Support or lead development of government and industry proposals for external funding
- Prepare and present/publish research results.
Requirements include demonstrated ability to perform primary responsibilities, and:
- BS in electrical or mechanical engineering (or closely related field)
- Minimum 5 years of work experience directly related to development of PHM technologies or data analytics solutions
- Demonstrated ability to conduct applied research
- Analytical ability to solve challenging design/development problems
- Experience with analytical modeling tools such as Python scientific ecosystem, and Matlab, and/or R
- Strong organization and motivational skills
- Strong verbal and written communication skills
Preferred qualifications include
- MS or PhD degree
- >10 years of directly related work experience
- Familiarity Strong working knowledge withof machine learning technologies and tools
- Working knowledge of system-simulation tools (Simulink/Modelica)
- Experience with finite element analysis, with special interest in failures (e.g. FRANC and FRANC 2D)